labelme批量json_to_dataset转换并解决无生成yaml文件问题

关键代码

# 最前面加入导包
import yaml

# 中间是代码的主体部分就不贴了
# 然后在最下面main函数之前加上这一部分：
    logger.warning('info.yaml is being replaced by label_names.txt')
    info = dict(label_names=label_names)
    with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
        yaml.safe_dump(info, f, default_flow_style=False)
    logger.info('Saved to: {}'.format(out_dir))

# 下面就是main函数了
if __name__ == '__main__':
    main()

count = os.listdir(json_dir)
    for i in range(0, len(count)):
        path = os.path.join(json_dir, count[i])

        if os.path.isfile(path):

完整代码
把整个文件代码替换就行

然后执行

labelme_json_to_dataset dir(你自己的文件夹路径)

import argparse
import base64
import json
import os
import os.path as osp

import imgviz
import PIL.Image

from labelme.logger import logger
from labelme import utils
import yaml

def main():
    logger.warning(
        "This script is aimed to demonstrate how to convert the "
        "JSON file to a single image dataset."
    )
    logger.warning(
        "It won't handle multiple JSON files to generate a "
        "real-use dataset."
    )

    parser = argparse.ArgumentParser()
    parser.add_argument("json_dir")
    parser.add_argument("-o", "--out", default=None)
    args = parser.parse_args()

    json_dir = args.json_dir


    count = os.listdir(json_dir)
    for i in range(0, len(count)):
        path = os.path.join(json_dir, count[i])

        if os.path.isfile(path):
            if args.out is None:
                out_dir = osp.basename(path).replace(".", "_")
                out_dir = osp.join(osp.dirname(path), out_dir)
            else:
                out_dir = args.out
            if not osp.exists(out_dir):
                os.mkdir(out_dir)
            data = json.load(open(path))
            imageData = data.get("imageData")

            if not imageData:
                imagePath = os.path.join(os.path.dirname(json_dir), data["imagePath"])
                with open(imagePath, "rb") as f:
                    imageData = f.read()
                    imageData = base64.b64encode(imageData).decode("utf-8")
            img = utils.img_b64_to_arr(imageData)

            label_name_to_value = {"_background_": 0}
            for shape in sorted(data["shapes"], key=lambda x: x["label"]):
                label_name = shape["label"]
                if label_name in label_name_to_value:
                    label_value = label_name_to_value[label_name]
                else:
                    label_value = len(label_name_to_value)
                    label_name_to_value[label_name] = label_value
            lbl, _ = utils.shapes_to_label(
                img.shape, data["shapes"], label_name_to_value
            )

            label_names = [None] * (max(label_name_to_value.values()) + 1)
            for name, value in label_name_to_value.items():
                label_names[value] = name

            lbl_viz = imgviz.label2rgb(
                label=lbl, img=imgviz.asgray(img), label_names=label_names, loc="rb"
            )

            PIL.Image.fromarray(img).save(osp.join(out_dir, "img.png"))
            utils.lblsave(osp.join(out_dir, "label.png"), lbl)
            PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, "label_viz.png"))

            with open(osp.join(out_dir, "label_names.txt"), "w") as f:
                for lbl_name in label_names:
                    f.write(lbl_name + "\n")

            logger.info("Saved to: {}".format(out_dir))
            logger.warning('info.yaml is being replaced by label_names.txt')
            info = dict(label_names=label_names)
            with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
                yaml.safe_dump(info, f, default_flow_style=False)
            logger.info('Saved to: {}'.format(out_dir))

if __name__ == "__main__":
    main()